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Short-Term Peak Power Changes in Adolescents of Similar Anthropometric Characteristics

MARTIN, RONAN J. F.; DORÉ, ERIC; HAUTIER, CHRISTOPHE A.; VAN PRAAGH, EMMANUEL; BEDU, MARIO

Medicine & Science in Sports & Exercise: August 2003 - Volume 35 - Issue 8 - pp 1436-1440
APPLIED SCIENCES: Physical Fitness and Performance

MARTIN, R. J. F., E. DORÉ, C. A. HAUTIER, E. VAN PRAAGH, and M. BEDU. Short-Term Peak Power Changes in Adolescents of Similar Anthropometric Characteristics. Med. Sci. Sports Exerc., Vol. 35, No. 8, pp. 1436–1440, 2003.

Purpose: The present study was undertaken to examine changes of cycling peak power (Pmax), optimal pedaling frequency (Vopt), and optimal pedaling force (Fopt) with age in subjects with the same lean leg volume (LLV), leg length (LL), and percentage body fat (%BF).

Method: A total of 132 males aged 9.5–16.5 volunteered for this study. The population was divided into prepubertal (G1), pubertal (G2), and postpubertal (G3) groups. Within G1, G2, and G3, although the subjects were divided into three different age subgroups, there were no significant differences for LLV, %BF, and LL.

Results: Results showed that within G1, G2, and G3, Pmax increased significantly with age. Optimal velocity (Vopt) increased significantly with age in G1, whereas optimal force (Fopt) increased significantly with age into the other groups (G2 and G3).

Conclusion: This study demonstrated that when anthropometric characteristics were controlled (LLV, LL, and %BF), Pmax and its two components (Vopt and Fopt) still increased with age. This indicates that other factors of qualitative nature have to be considered when determining Pmax, Vopt, and Fopt.

Because of the prohibition against invasive techniques, direct measurement of children’s and adolescents’ anaerobic metabolism during exercise was not ethically possible, and research efforts have focused on the measurement of maximal short-term power output. The “force-velocity” test (1,3,8,9,11,29), which allows the determination of maximal short-term leg peak power (Pmax) and its two components (optimal pedaling frequency, Vopt, and optimal pedaling force, Fopt) during sprint cycling, has emerged as a valid test for adults as well as for children. Numerous studies, using longitudinal or cross-sectional methods, have provided evidence that Pmax increased during growth. The determinants of Pmax during growth were related to quantitative and qualitative muscular factors. Van Praagh and Doré (28) reviewed studies based on the qualitative muscular factors and showed that fiber differentiation, contractile properties, motor coordination, endocrinologic, biomechanical, and genetic characteristics were involved in the increase of Pmax. However, these studies were often conflicting, and no definite conclusion can be drawn because they were based on a limited number of subjects due to the use of invasive techniques. The effect of quantitative muscular factors on Pmax is better known. In young male children, Mercier et al. (19) showed that lean body mass explained 88% of the total variance of maximal anaerobic power. Recently, Doré et al. (9) studied 530 young male children and demonstrated that lean leg volume (LLV) was well related to the total variance of short-term leg peak power (88.2%). Bedu et al. (3) and Vandewalle et al. (29) showed that Vopt increased with age. However, Martin and Spirduso (17) and Martin et al. (18) demonstrated that Vopt was related to leg length (LL). Concerning Fopt, Doré et al. (9) showed that LLV was the factor that best explained its total variance. Qualitative and quantitative factors are bound, and until now, it was difficult to determine what was the importance of each factors in the increase of Pmax with age and to establish whether the influence of these factors remained the same before, during, and after puberty. One scientific strategy could consist in isolating quantitative muscular factors at these three stages and examining the effect of age on Pmax. The aim of this study was to highlight the effect of qualitative factors on Pmax, in determining the effect of age on this parameter and its two components in boys with the same quantitative factors (LLV, percentage body fat (%BF), and LL) at different growth periods.

Laboratory of Exercise Physiology, Gabriel Montpied Hospital, Clermont-Ferrand, FRANCE

Address for correspondence: Mario Bedu, Laboratory of Exercise Physiology, Gabriel Montpied Hospital, B.P0.69-63003 Clermont-Ferrand Cedex 1, France; E-mail: mbedu@chu-clermontferrand.fr.

Submitted for publication September 2002.

Accepted for publication April 2003.

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METHODS

Subjects.

A total of 132 males aged 9.5–16.5 volunteered for this study. They represented a subset of individuals involved in a larger investigation (9). These individuals were recruited from four different elementary, secondary, or high schools. Before the study, each subject was fully informed of the purpose, protocol, and procedure of the study and any associated risks, with all parents signing informed consent forms. The protocol was approved by the Ethics Committee of the Auvergne University.

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Experimental design.

The population was divided into three groups according to their stages: prepubertal (G1), pubertal (G2), and postpubertal (G3) (27). The LLV, mass, height, and LL mean values were significantly different between G1, G2, and G3 (P < 0,05). Within each group (G1, G2, and G3), the subjects were divided into three significantly different age subgroups. Despite that, there were no significant differences for LLV, %BF, and LL. Anthropometric characteristics are given in Table 1.

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Protocol.

Each individual participated in two sessions conducted during physical education lessons. The first session was used for anthropometric measurements. Measurements included height (H), body mass (BM), and LL (standing − sitting height). Subscapular and tricipital skinfold thicknesses were taken using a Harpenden skinfolds caliper. %BF was estimated using Slaughter’s equations (26). %BF was chosen as a discriminating factor to limit errors in LLV measurement. LLV was assessed by anthropometry (13). That technique consists in partitioning the leg volume into six segments which are similar to truncated cones. This method was validated for adults (13) as well as for children (7).

The second session was used for a short-term cycling power test (force-velocity test) on a calibrated friction-loaded ergometer (Ergomeca, Sorem, Toulon, France) that presented the following features: 0.17-m crank length and a development of 6.12 m per pedal revolution. An opto-electrical sensor measured the rolling displacement of the flywheel four times per revolution (or 16 times per pedal revolution). A second sensor allowed the detection of the beginning of the crank gear rotation cycle. Before the test, all subjects completed a practice session. The test consisted of three short “all-out” sprints (5- to 8-s duration) against different braking loads applied in a randomized order: 2.5, 5.0, and 7.5% body mass. Each subject was asked to pedal as fast as possible until maximal velocity was reached (5- to 8-s duration). They were told to remain seated on the saddle throughout the test. Toe clips were used to prevent the feet from slipping. At least 3-min rest was allowed between each sprint.

During the flywheel acceleration, the subjects had to produce a total external force dependent on two components: (i) a constant frictional force against the braking load applied at the rim of the flywheel, and (ii) an inertial force necessary to accelerate the flywheel and dependent on the variation of the kinetic energy of the latter. From a single sprint, concomitant measurement of force, velocity, and power was obtained, and maximal power was attained during the acceleration phase. Previously, the flywheel inertia had been determined using the method described by Lakomy (15). Instantaneous power was calculated according to the product of total external force and pedaling rate and was averaged per half-pedal revolution. To obtain Pmax data over the largest range of velocities, the individual power-velocity relationships were drawn from combined values of the three sprints (1). Cycling peak power (Pmax) was defined as the apex of the power-velocity relationship. The optimal force (Fopt; N) and pedaling frequency (Vopt, rpm) corresponded to the force and pedaling frequency at Pmax. In adolescents and adults, it has been found that Pmax does not depend on the braking load applied to the rim of the flywheel (1,15). However, in children aged 8–13, Doré et al. (8) showed that a braking load of 7.5% body mass was too high in children to attain Vopt, and consequently Pmax. Nevertheless, in this study, the braking load of 7.5% body mass was included in the protocol and was cancelled in children when they failed to attain their Vopt (8).

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Statistics.

Results were expressed as mean and standard deviation (SD). Comparisons between G1, G2, and G3 and the effects of age on Pmax, Vopt, and Fopt within G1, G2, and G3 were analyzed by ANOVA (Stat View SE+Graphics, Abacus Concept, Inc.). When the ANOVA test was significant, a post hoc comparison analysis (Newman-Keuls) was used to determine differences between all age groups. All data sets were checked for normality of distribution and homogeneity of variance. Significance level was set at P < 0.05. The effect of age on Pmax, Vopt, and Fopt within G1, G2, and G3 were also evaluated using linear regression analysis. The level of significance was set at P < 0.05.

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RESULTS

Pmax.

Within G1, G2, and G3, Pmax was significantly correlated with age (Table 2).

In G1 (Fig. 1A), average Pmax values (Table 3) increased significantly (17.2%; P < 0.05) between the lowest and the highest age group, and it was 14.0% higher (P < 0.05) at 11 compared with 10-yr-old boys. There was no significant difference (P = 0.62) between 11 and 12 yr olds.

In G2, mean Pmax value increased significantly (19.8%; P < 0.05) between the lowest and the highest age group, and it was 15.7% higher (P < 0.05) at 13 compared with 12 yr olds. There was no significant difference (P = 0.56) between 13 and 14 yr olds.

In G3, mean Pmax value was 14.2% higher (P < 0.05) at 16 compared with 14 yr olds. There were no significant differences between 14 and 15 (P = 0.11) and 15 and 16 yr olds (P = 0.40).

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Vopt.

In G1, Vopt was significantly correlated with age, whereas there were no significant correlations within G2 and G3 (Table 2).

In G1 (Fig. 1B), mean Vopt value (Table 3) was 9.3% higher (P < 0.05) at 12 compared with 10 yr and 8.3% higher (P < 0.05) at 12 compared with 11 yr olds. There were no significant differences between 10 and 11 yr olds (P = 0.78).

In G2, mean Vopt value increased significantly (6.6%; P < 0.05) between the lowest and the highest age group. There were no significant differences between 12 and 13 (P = 0.40) and 13 and 14 yr olds (P = 0.10).

In G3, there were no significant differences between 14 and 15 (P = 0.45), 14 and 16 (P = 0.68), and 15 and 16 yr olds (P = 0.73).

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Fopt.

In G2 and G3, Fopt was significantly correlated with age, whereas it was not the case in G1 (Table 2).

In G1 (Fig. 1C), mean Fopt values (Table 3) were 13.2% higher (P < 0.05) at 11 compared with 10 yr olds. There were no significant differences between 10 and 12 (P = 0.19) and 11 and 12 yr olds (P = 0.27).

In G2, mean Fopt value was 13.1% higher (P < 0.05) at 13 compared with 12 yr olds and 12.2% higher (P < 0.05) at 14 compared to 12 yr olds. There were no significant differences between 13 and 14 yr olds (P = 0.83).

In G3, mean Fopt value increased significantly (13.2%; P < 0.05) between the lowest and the highest age group. There were no significant differences between 14 and 15 (P = 0.16) and 15 and 16 yr olds (P = 0.23).

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DISCUSSION

The aim of the study was to highlight the effect of qualitative factors on Pmax, in determining the effect of age on this parameter and its two components in boys with the same quantitative factors (LLV, %BF, and LL) at different growth periods. The results showed that in the prepubertal (G1), pubertal (G2), and postpubertal (G3) groups, Pmax increase with age. In G1, the increase of Pmax is related to the increase of Vopt, whereas in G2 and G3 it is associated with the increase of Fopt.

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Influence of age on Pmax.

According to Doré et al. (9), LLV was considered the most appropriate variable for the standardization of Pmax in cycling. This is also in agreement with studies reported by Davies et al. (7), Sargeant and Davies (23), and Blimkie et al. (4), who reported that standardization should be based on the size of the effective muscles involved in short-term power measurement. In the present study, in each age group, Pmax values normalized for body mass were 15% lower than those measured by Doré et al. (9). Although we used the same protocol, the reduction might be explained by a difference in the method of calculation. Doré et al. (9) considered Pmax as the highest peak power of the short “all-out” sprints, whereas in this study, Pmax was measured as the apex of the power-velocity relationship drawn with the velocity and power data of the three sprints (1).

Figure 1A shows that within G1, G2, and G3 mean Pmax values increased with age. In G2 and G3, the increase could be associated with the adolescent spurt, which occurs around 14 yr in boys (27). The adolescent spurt is accompanied by changes in muscle characteristics that may influence Pmax. In the vastus lateralis muscle, the percentage of Type II fibers is lower in early childhood compared with adulthood (6) and attains adult proportions during late adolescence (10). In the same way, Jansson (12) reported an inverse U-shape relation between percentage fiber I and age (from birth to 35 yr old) with a maximum at 9 yr. In the quadriceps of the human adult, Larsson and Moss (16) demonstrated that Type II fibers have greater maximum shortening velocity and greater maximal force production. If these contractile properties are present in all maturity stages, then the increase of fast fiber distribution may explain the increase of Pmax in G2 and G3. Recently, the use of 31PNMRS (phosphorus magnetic nuclear resonance spectroscopy) has provided a noninvasive technique to explore muscle metabolism at rest, during exercise and recovery (28). Zanconato et al. (30) and Kuno et al. (14) both using 31PNMRS reported that children and adolescents have lower glycolytic ability during high-intensity exercise than adults. Although there is a lack of knowledge concerning the exact kinetics of glycolytic ability changes with age, it may explain the increase of Pmax within G2 and G3.

Conversely, the increase of Pmax observed in G1 may not be explained by changes induced by puberty. However, changes that occur during this period in neurological factors may influence Pmax. It is at puberty that the pyramidal system attains full functional maturity and the subject becomes capable of developing high-intensity coordinated movements (2). According to Astrand (2), the longitudinal study of Seefeldt and Haubenstricker (25) demonstrated that 60% of children reach the mature pattern for standing long jump at about 9–10 yr. In our study, it was suggested that the fact that 10-yr-old boys have not yet mastered the basic movement of cycling could explain that their mean Pmax values are significantly (P < 0.05) lower than that of 11- and 12-yr-old boys. The role that age might play on motor coordination and full activation of muscle motor units will be discussed in the following paragraphs.

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Influence of age on Vopt.

Because it was shown that during cycling ergometry Vopt was strongly related to leg length (LL) (9,17,18) when using the same crank arm length, the data in the literature regarding the increase of Vopt with age must be reconsidered.

Figure 1B and Table 2 show that Vopt increased significantly within prepubertal group (G1), whereas there were no significant increases within pubertal (G2) and postpubertal (G3) groups. Based on the study of Hautier et al. (11), which showed a strong relationship between the fiber composition of knee extensors and Vopt, the increase of Vopt may be related to modifications in the proportion of fast-twitch fibers in the vastus lateralis muscle. However, in this study, the increase of Vopt might be related to motor control changes rather than muscle fiber type composition changes. Mero (20) reported that “the development of motor coordination provides a large basis on which to improve skills, and especially speed ability in many sports events.” According to Astrand (2), the increase in the functional maturity of the pyramidal system between 9 and 12 yr olds may contribute to optimize the motor coordination in cycling movements.

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Influence of age on Fopt.

Figure 1C and Table 2 showed that Fopt increased significantly after puberty in G2 and G3. This observation cannot be attributed to fiber type changes because Sargeant (24) reported that, for the same muscle cross-sectional area, fast fiber twitch and slow fiber twitch presented the same specific isometric force. Based on the hypothesis that there is a physiological reserve of force-generating ability, changes in Fopt might be explained by the increased ability to fully activate the motor units of muscle that are involved in cycling movements. In preadolescent boys, interpolated twitch technique (22) or electromyography methods (21) have been used to assess the contribution of motor unit activation to training-induced strength increase. In monoarticular movements, they provide evidence that strength gains are, at least in part, attributable to increase in motor-unit activation. In a complex multi-joint exercise such as cycling movement, this evidence is reinforced and may explain why in our study Fopt increased in each LLV group. Changes in the effectiveness, which in cycling is defined as the ratio between the force “used” in propulsion (perpendicular to the crank) and the force “applied” by the subject, may also be added as a contributing factor (5).

In conclusion, this study demonstrated that in groups of similar LLV, LL, and %BF Pmax increased by 17.2%, 19.8%, and 14.2% between 10 and 12, 12 and 14, and 14 and 16 yr olds, respectively. Furthermore, the results showed that the increase of Pmax in the prepubertal group was accompanied by a 9.3% increase of Vopt, whereas the increase of Pmax in the pubertal and postpubertal groups was accompanied by an increase of Fopt by 12.2% and 13.2%, respectively. This indicates that, when anthropometric characteristics are controlled, Pmax still increases with age and is related to the improvement of one of its two components (i.e., Vopt and Fopt). Further investigations are needed to explore qualitative factors (fiber type composition, glycolytic ability, motor coordination, motor unit activation, and effectiveness), which variables may contribute to the age effect on Pmax, Vopt, and Fopt.

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Medicine & Science in Sports & Exercise, 36(3): 498-503.

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Keywords:

CHILDREN; OPTIMAL PEDALING FREQUENCY; OPTIMAL PEDALING FORCE; CYCLING ERGOMETER; PUBERTY

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